It check for the key-value pairs in the dict object. We normalize the dict object using the normalize_json() function.It offers a lot of functionalities and operations that can be performed on the dataframe. It performs operations by converting the data into a pandas.DataFrame format. Pandas is a free source python library used for data manipulation and analysis. The same can be achieved through the use of Pandas Python library. "title": "IT stocks to see a jump this month", In the final step, we write the CSV data generated in the earlier step to a preferred location provided through the filepath parameter.This function concatenates each record using a comma (,) and then all these individual records are appended with a new line (ā\nā in python). The desired CSV data is created using the generate_csv_data() function.If the value is again a dict then it concatenates the key string with the key string of the nested dict. It checks for the key-value pairs in the dict object. The read_json() function is used for the task, which taken the file path along with the extension as a parameter and returns the contents of the JSON file as a python dict object. This will help us to make use of python dict methods to perform some operations.
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